Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty

•Designing a novel sustainable closed-loop supply chain with routing and inventory.•Applying a stochastic-possibilistic programming method to cope with the uncertainty.•Developing a new hybrid meta-heuristic algorithm to efficiently solve the problem.•Applicability of the model is tested on a real c...

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Bibliographic Details
Published in:Transportation research. Part E, Logistics and transportation review Logistics and transportation review, 2016-05, Vol.89, p.182-214
Main Authors: Zhalechian, M., Tavakkoli-Moghaddam, R., Zahiri, B., Mohammadi, M.
Format: Article
Language:English
Subjects:
Algorithms
Closed-loop supply chain
Computer Science
Discrete Mathematics
Economics
Environmental impact
Heuristic
Impact analysis
Inventory
Meta-heuristic
Networks
Operations Research
Queuing theory
Routing
Social impact
Stochastic models
Studies
Supply chains
Sustainability
Sustainable design
Transportation
Uncertainty
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Summary:•Designing a novel sustainable closed-loop supply chain with routing and inventory.•Applying a stochastic-possibilistic programming method to cope with the uncertainty.•Developing a new hybrid meta-heuristic algorithm to efficiently solve the problem.•Applicability of the model is tested on a real case study. Considering economic, environmental and social impacts, this paper presents a new sustainable closed-loop location-routing-inventory model under mixed uncertainty. The environmental impacts of CO2 emissions, fuel consumption, wasted energy and the social impacts of created job opportunities and economic development are considered in this paper. The uncertain nature of the network is handled using a stochastic-possibilistic programming approach. Furthermore, for large-sized problems, a hybrid meta-heuristic algorithm and lower bounds are developed and discussed. Finally, a real case study is provided to demonstrate the applicability of the model in real-world applications, and several in-depth analyses are conducted to develop managerial implications.
ISSN:1366-5545
1878-5794
DOI:10.1016/j.tre.2016.02.011